Robust Quantum Control via the Dark State: Adiabatic Population Engineering in a Three-Level Λ System
- Rosario Aldava Asencios¹
- Pedro Rojas Fernández¹
- Teófilo Vargas Auccalla¹
- Ricardo Quispe-Mendizábal¹,²
¹ GFT & QuantumQuipu, Universidad Nacional Mayor de San Marcos
² Universidad de Santiago de Chile
This repository contains computational implementations for quantum control in a three-level Lambda (Λ) system using dark state techniques and adiabatic population engineering. The work explores robust quantum control strategies that leverage the dark state to achieve efficient population transfer in atomic systems.
The repository includes two Jupyter notebooks with identical content in different languages:
(ENG)_ControlCuantico_SistemaLambda.ipynb- English version(ESP)_ControlCuantico_SistemaLambda.ipynb- Spanish version (Versión en español)
The Lambda system is a fundamental configuration in quantum optics consisting of three energy levels where two ground states are coupled to an excited state via two laser fields. This project implements:
- Adiabatic Evolution: Techniques for slowly varying control parameters to maintain the system in a dark state
- Population Engineering: Methods for robust population transfer between quantum states
- Dark State Control: Utilization of the dark state for loss-free quantum state manipulation
- Numerical Simulations: Complete implementation of the quantum dynamics and control protocols
- Lambda (Λ) System: A three-level quantum system with two ground states and one excited state
- Dark State: A quantum superposition that decouples from the excited state, preventing spontaneous emission
- Adiabatic Process: Slow evolution that keeps the system in an instantaneous eigenstate
- STIRAP (Stimulated Raman Adiabatic Passage): A robust population transfer technique
The notebooks require standard Python scientific computing libraries:
- NumPy
- SciPy
- Matplotlib
- QuTiP (Quantum Toolbox in Python)
- Clone this repository
- Install the required dependencies
- Open either notebook depending on your language preference
- Run the cells sequentially to reproduce the simulations and results
The techniques demonstrated in this work have applications in:
- Quantum computing and quantum information processing
- Quantum state preparation and manipulation
- Atomic and molecular physics
- Quantum optics experiments
- Robust control in the presence of noise and decoherence
This project is part of academic research conducted at Universidad Nacional Mayor de San Marcos
If you use this code in your research, please cite the original work and acknowledge the authors and their institutions.
For questions or collaborations, please contact the authors through their respective institutions:
- GFT & QuantumQuipu, Universidad Nacional Mayor de San Marcos
- Universidad de Santiago de Chile